OEE approach applied to additive manufacturing systems in distributed manufacturing networks

Abstract

Technological changes are transforming business models, such as distributed manufacturing networks, which have benefited from additive manufacturing (AM) to transform centralized into decentralized production. The main challenges of these networks are related to their global performance, which depends on several factors such as production responsiveness, machine efficiency, printing quality and the operation of equipment, which can suffer from unscheduled downtime. Decision support tools, such as optimization and simulation can contribute to an effective response to these challenges. To obtain a more precise performance evaluation this work proposes a methodology for Overall Equipment Effectiveness (OEE) as a decision-making approach in distributed manufacturing networks based on additive manufacturing, exploring technologies from industry 4.0 applied in the context of the production systems digitization in flexible markets. Using OEE to optimize the smart additive manufacturing units (SAMs) - a concept of an AM network - the demand of four cities in Brazil are distributed according to their performance in terms of lead-time, adjusted to the real expected performance, demonstrating that on average, a decreasing of 44% in OEE impacted in an increment of 75% in the total lead-time for parts delivering, changing the decision-making for order allocation in a distributed manufacturing network.